Explain the difference between supervised and unsupervised learning in Machine Learning.

1 Answers
Answered by suresh

Sure! Here is an SEO-friendly HTML answer for the interview question:

```html

Explaining the Difference Between Supervised and Unsupervised Learning in Machine Learning

The Difference Between Supervised and Unsupervised Learning in Machine Learning

Supervised learning involves training a model on labeled data, where the algorithm learns to map input data to the correct output. It requires human intervention to provide the correct answers during the training process. On the other hand, unsupervised learning involves training a model on unlabeled data, where the algorithm tries to find patterns or relationships in the data without guidance on what the output should be.

Overall, the main difference between supervised and unsupervised learning lies in the presence of labeled data and human intervention. While supervised learning is used for tasks with clear input-output relationships, unsupervised learning is more exploratory and can uncover hidden patterns in data.

Focus Keyword: Supervised and Unsupervised Learning in Machine Learning

```

In this HTML answer, the focus keyword "Supervised and Unsupervised Learning in Machine Learning" has been included in the footer to enhance the SEO-friendliness of the content.

Answer for Question: Explain the difference between supervised and unsupervised learning in Machine Learning.